As mentioned earlier, the focus of this thesis was on the overall workflow of modelling and reasoning about context-based domain models, but we also observe several linking points for
future research. When investigating LM⟦LO⟧ , we mainly focused on the consistency problem, which was central for our goal. Besides that, query answering with context DLs would be an interesting direction for further investigations. Recently, there has been a lot of work in the area of temporal query answering. As our approach shares a similar setting, we are sure that there is plenty of motivation, applications and methods available to analyse contextualised query answering. Furthermore, there is current work on role-based databases[JKV+16], i.e. database systems that are based on a conceptual, role-based data model to natively represent complex data. Due to the close connection of query answering and database theory, it might be worth investigating query answering involving role-based database systems.
Going back to the consistency problem, we still think one can narrow the gap to undecid- ability. We added contextualised concepts to LM⟦LO⟧ which results in undecidability in the presence of rigid roles. Quite certain, there are other, probably more restrictive, means to further extend the expressive power of the logic while preserving decidable.
Another extension to LM⟦LO⟧ could be towards temporal logics. The combinations of DLs with temporal logics, point-based or interval, are well understood. As both temporal and contextualised DLs adopt a possible worlds semantics, it seems natural to also combine temporal logics with contextualised DLs. On a more abstract level, it might be even possible to analyse common properties of these combinations and deduce an abstract combination of DLs with itself or with other logics. Then temporal DLs or contextualised DLs could be an instance of that abstract combination.
The presented mapping for role-based models is based on the Compartment Role Object Model (CROM). As CROM might be extended in the future, for example by new kinds of constraints, there is always some future work to analyse these upcoming features and to investigate whether they can also be represented by a contextualised DL ontology. Besides that, an investigation where contextualised DLs can be used except for CROM will help to detect any missing expressiveness of LM⟦LO⟧ if existent.
The last starting point for future work would be the reasoner. While we used a black box approach, combined or integrated (tableaux) algorithms for deciding consistency are conceivable. A different optimisation would be an even more goal-oriented reasoner, which behaves especially well for contextualised ontologies produced from CROM models. Since, for example, the validation of role groups is rather of combinatorial nature which is quite hard for DL reasoners, it might be useful to use SAT solvers internally to improve overall performance.
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